Field x Level
EHI righties (n = 378)
In all EHI-confirmed righties (EHI > 40), do we see the predicted
field by level interaction?
Summary.
We see the predicted effect, for both reaction time (27.31ms, 95%CI
[19.80, 34.82], p < .001) and accuracy (OR = 1.76, 95%CI [1.49,
2.09], p < .001).
Reaction time
Plots


Statistics
Reaction time is modeled as a linear effect of field and level, using
data from every target-present trial with a “go” response:
lmer( rt ~ field + level + field:level + (1 | subject) )
| npar |
AIC |
BIC |
logLik |
deviance |
Chisq |
Df |
p.value |
| 5 |
622,246.898 |
622,290.581 |
−311,118.449 |
622,236.898 |
- |
- |
- |
| 6 |
622,198.195 |
622,250.613 |
−311,093.097 |
622,186.195 |
50.704 |
1 |
<.0001 |
| term |
df |
sumsq |
meansq |
statistic |
p.value |
| field |
1 |
10,025.524 |
10,025.524 |
0.139 |
.71 |
| level |
1 |
4,773,142.048 |
4,773,142.048 |
66.337 |
<.0001 |
| field:level |
1 |
2,100,773.834 |
2,100,773.834 |
29.197 |
<.0001 |
| Residuals |
45,997 |
3,309,615,140.279 |
71,952.848 |
- |
- |
| field_consec |
level_consec |
estimate |
SE |
df |
asymp.LCL |
asymp.UCL |
z.ratio |
p.value |
| LVF - RVF |
Local - Global |
27.308 |
3.834 |
Inf |
19.793 |
34.822 |
7.122 |
<.0001 |
| contrast |
estimate |
SE |
df |
asymp.LCL |
asymp.UCL |
z.ratio |
p.value |
| LVF Local - LVF Global |
34.549 |
2.71 |
Inf |
29.238 |
39.86 |
12.75 |
<.0001 |
| RVF Local - RVF Global |
7.242 |
2.714 |
Inf |
1.922 |
12.561 |
2.668 |
.008 |
| field |
level |
emmean |
SE |
df |
asymp.LCL |
asymp.UCL |
| LVF |
Global |
667.092 |
9.111 |
Inf |
649.234 |
684.95 |
| LVF |
Local |
701.641 |
9.119 |
Inf |
683.769 |
719.514 |
| RVF |
Global |
682.117 |
9.114 |
Inf |
664.253 |
699.981 |
| RVF |
Local |
689.359 |
9.117 |
Inf |
671.489 |
707.228 |
| field |
level |
median |
mean |
SE |
| LVF |
Global |
622 |
665.601 |
2.441 |
| LVF |
Local |
657 |
699.47 |
2.558 |
| RVF |
Global |
638 |
679.765 |
2.52 |
| RVF |
Local |
650 |
686.601 |
2.488 |
Accuracy
Plots


Statistics
Accuracy is modeled as a binomial effect of field and level, using
binary correct/incorrect data from every target-present trial:
glmer( correct ~ field + level + field:level + (1 | subject), family = "binomial" )
| npar |
AIC |
BIC |
logLik |
deviance |
Chisq |
Df |
p.value |
| 4 |
17,546.443 |
17,581.59 |
−8,769.221 |
17,538.443 |
- |
- |
- |
| 5 |
17,507.988 |
17,551.923 |
−8,748.994 |
17,497.988 |
40.454 |
1 |
<.0001 |
| field_consec |
level_consec |
odds.ratio |
SE |
df |
asymp.LCL |
asymp.UCL |
null |
z.ratio |
p.value |
| RVF / LVF |
Local / Global |
1.762 |
0.154 |
Inf |
1.485 |
2.092 |
1 |
6.477 |
<.0001 |
| contrast |
odds.ratio |
SE |
df |
asymp.LCL |
asymp.UCL |
null |
z.ratio |
p.value |
| LVF Global / LVF Local |
2.312 |
0.149 |
Inf |
2.037 |
2.624 |
1 |
12.976 |
<.0001 |
| RVF Global / RVF Local |
1.312 |
0.078 |
Inf |
1.168 |
1.473 |
1 |
4.592 |
<.0001 |
| field |
level |
prob |
SE |
df |
asymp.LCL |
asymp.UCL |
| LVF |
Global |
0.981 |
0.001 |
Inf |
0.977 |
0.983 |
| LVF |
Local |
0.956 |
0.003 |
Inf |
0.95 |
0.961 |
| RVF |
Global |
0.971 |
0.002 |
Inf |
0.966 |
0.974 |
| RVF |
Local |
0.962 |
0.003 |
Inf |
0.957 |
0.966 |
| field |
level |
mean_subject_percent_correct |
| LVF |
Global |
96.974 |
| LVF |
Local |
93.51 |
| RVF |
Global |
95.527 |
| RVF |
Local |
94.287 |
EHI mixedies (n = 135)
In all EHI-confirmed mixed handers (-40 < EHI < +40), do we see
a field by level interaction?
Summary. We see a smaller effect in the same
direction as right handers’ for reaction time (21.66ms, 95%CI [9.26,
34.06], p < .001). For accuracy, we see a smaller, non-significant
effect in the same direction as right handers’ (OR = 1.10, 95%CI [0.82,
1.47], p = .53).
Reaction time
Plots


Statistics
Reaction time is modeled as a linear effect of field and level, using
data from every target-present trial with a “go” response:
lmer( rt ~ field + level + field:level + (1 | subject) )
| npar |
AIC |
BIC |
logLik |
deviance |
Chisq |
Df |
p.value |
| 5 |
221,359.298 |
221,397.824 |
−110,674.649 |
221,349.298 |
- |
- |
- |
| 6 |
221,349.576 |
221,395.807 |
−110,668.788 |
221,337.576 |
11.722 |
1 |
.0006 |
| term |
df |
sumsq |
meansq |
statistic |
p.value |
| field |
1 |
12,184.492 |
12,184.492 |
0.181 |
.67 |
| level |
1 |
3,074,358.85 |
3,074,358.85 |
45.607 |
<.0001 |
| field:level |
1 |
533,994.492 |
533,994.492 |
7.922 |
.005 |
| Residuals |
16,398 |
1,105,383,522.567 |
67,409.655 |
- |
- |
| field_consec |
level_consec |
estimate |
SE |
df |
asymp.LCL |
asymp.UCL |
z.ratio |
p.value |
| LVF - RVF |
Local - Global |
21.658 |
6.325 |
Inf |
9.261 |
34.055 |
3.424 |
.0006 |
| contrast |
estimate |
SE |
df |
asymp.LCL |
asymp.UCL |
z.ratio |
p.value |
| LVF Local - LVF Global |
37.017 |
4.474 |
Inf |
28.249 |
45.785 |
8.274 |
<.0001 |
| RVF Local - RVF Global |
15.359 |
4.474 |
Inf |
6.589 |
24.128 |
3.433 |
.0006 |
| field |
level |
emmean |
SE |
df |
asymp.LCL |
asymp.UCL |
| LVF |
Global |
620.908 |
14.561 |
Inf |
592.369 |
649.447 |
| LVF |
Local |
657.925 |
14.575 |
Inf |
629.359 |
686.491 |
| RVF |
Global |
632.664 |
14.562 |
Inf |
604.124 |
661.204 |
| RVF |
Local |
648.023 |
14.574 |
Inf |
619.458 |
676.587 |
| field |
level |
median |
mean |
SE |
| LVF |
Global |
570 |
619.02 |
3.887 |
| LVF |
Local |
603 |
657.818 |
4.186 |
| RVF |
Global |
588 |
631.927 |
4.019 |
| RVF |
Local |
599 |
647.899 |
4.132 |
Accuracy
Plots


Statistics
Accuracy is modeled as a binomial effect of field and level, using
binary correct/incorrect data from every target-present trial:
glmer( correct ~ field + level + field:level + (1 | subject), family = "binomial" )
| npar |
AIC |
BIC |
logLik |
deviance |
Chisq |
Df |
p.value |
| 4 |
6,267.227 |
6,298.256 |
−3,129.614 |
6,259.227 |
- |
- |
- |
| 5 |
6,268.836 |
6,307.622 |
−3,129.418 |
6,258.836 |
0.392 |
1 |
.53 |
| field_consec |
level_consec |
odds.ratio |
SE |
df |
asymp.LCL |
asymp.UCL |
null |
z.ratio |
p.value |
| RVF / LVF |
Local / Global |
1.099 |
0.162 |
Inf |
0.823 |
1.468 |
1 |
0.639 |
.52 |
| contrast |
odds.ratio |
SE |
df |
asymp.LCL |
asymp.UCL |
null |
z.ratio |
p.value |
| LVF Global / LVF Local |
2.272 |
0.239 |
Inf |
1.848 |
2.792 |
1 |
7.796 |
<.0001 |
| RVF Global / RVF Local |
2.067 |
0.214 |
Inf |
1.687 |
2.533 |
1 |
7.004 |
<.0001 |
| field |
level |
prob |
SE |
df |
asymp.LCL |
asymp.UCL |
| LVF |
Global |
0.98 |
0.003 |
Inf |
0.974 |
0.985 |
| LVF |
Local |
0.956 |
0.005 |
Inf |
0.945 |
0.965 |
| RVF |
Global |
0.979 |
0.003 |
Inf |
0.973 |
0.984 |
| RVF |
Local |
0.957 |
0.005 |
Inf |
0.947 |
0.966 |
| field |
level |
mean_subject_percent_correct |
| LVF |
Global |
96.713 |
| LVF |
Local |
93.148 |
| RVF |
Global |
96.505 |
| RVF |
Local |
93.31 |
EHI lefties (n = 331)
In all EHI-confirmed lefties (EHI < -40), do we see a field by
level interaction?
Summary. We see a
smaller effect in the same direction as right handers’ for reaction time
(15.64ms, 95%CI [7.58, 23.70], p < .001). For accuracy, we see a
larger effect in the same direction as right handers (OR = 1.96, 95%CI
[1.63, 2.37], p < .001).
Reaction time
Plots


Statistics
Reaction time is modeled as a linear effect of field and level, using
data from every target-present trial with a “go” response:
lmer( rt ~ field + level + field:level + (1 | subject) )
| npar |
AIC |
BIC |
logLik |
deviance |
Chisq |
Df |
p.value |
| 5 |
544,097.107 |
544,140.116 |
−272,043.553 |
544,087.107 |
- |
- |
- |
| 6 |
544,084.643 |
544,136.254 |
−272,036.321 |
544,072.643 |
14.464 |
1 |
.0001 |
| term |
df |
sumsq |
meansq |
statistic |
p.value |
| field |
1 |
3,165,697.487 |
3,165,697.487 |
45.987 |
<.0001 |
| level |
1 |
4,819,463.357 |
4,819,463.357 |
70.01 |
<.0001 |
| field:level |
1 |
748,845.081 |
748,845.081 |
10.878 |
.001 |
| Residuals |
40,208 |
2,767,887,055.586 |
68,839.212 |
- |
- |
| field_consec |
level_consec |
estimate |
SE |
df |
asymp.LCL |
asymp.UCL |
z.ratio |
p.value |
| LVF - RVF |
Local - Global |
15.643 |
4.113 |
Inf |
7.582 |
23.704 |
3.803 |
.0001 |
| contrast |
estimate |
SE |
df |
asymp.LCL |
asymp.UCL |
z.ratio |
p.value |
| LVF Local - LVF Global |
29.357 |
2.907 |
Inf |
23.66 |
35.055 |
10.099 |
<.0001 |
| RVF Local - RVF Global |
13.715 |
2.915 |
Inf |
8.002 |
19.427 |
4.705 |
<.0001 |
| field |
level |
emmean |
SE |
df |
asymp.LCL |
asymp.UCL |
| LVF |
Global |
638.206 |
9.168 |
Inf |
620.237 |
656.174 |
| LVF |
Local |
667.563 |
9.179 |
Inf |
649.572 |
685.555 |
| RVF |
Global |
663.501 |
9.172 |
Inf |
645.524 |
681.478 |
| RVF |
Local |
677.216 |
9.178 |
Inf |
659.228 |
695.204 |
| field |
level |
median |
mean |
SE |
| LVF |
Global |
591 |
637.105 |
2.476 |
| LVF |
Local |
624 |
667.612 |
2.673 |
| RVF |
Global |
621 |
663.2 |
2.652 |
| RVF |
Local |
635 |
676.443 |
2.67 |
Accuracy
Plots


Statistics
Accuracy is modeled as a binomial effect of field and level, using
binary correct/incorrect data from every target-present trial:
glmer( correct ~ field + level + field:level + (1 | subject), family = "binomial" )
| npar |
AIC |
BIC |
logLik |
deviance |
Chisq |
Df |
p.value |
| 4 |
15,377.889 |
15,412.505 |
−7,684.944 |
15,369.889 |
- |
- |
- |
| 5 |
15,331.656 |
15,374.927 |
−7,660.828 |
15,321.656 |
48.232 |
1 |
<.0001 |
| field_consec |
level_consec |
odds.ratio |
SE |
df |
asymp.LCL |
asymp.UCL |
null |
z.ratio |
p.value |
| RVF / LVF |
Local / Global |
1.961 |
0.188 |
Inf |
1.626 |
2.366 |
1 |
7.04 |
<.0001 |
| contrast |
odds.ratio |
SE |
df |
asymp.LCL |
asymp.UCL |
null |
z.ratio |
p.value |
| LVF Global / LVF Local |
3.007 |
0.217 |
Inf |
2.609 |
3.464 |
1 |
15.222 |
<.0001 |
| RVF Global / RVF Local |
1.533 |
0.096 |
Inf |
1.355 |
1.734 |
1 |
6.799 |
<.0001 |
| field |
level |
prob |
SE |
df |
asymp.LCL |
asymp.UCL |
| LVF |
Global |
0.984 |
0.001 |
Inf |
0.981 |
0.986 |
| LVF |
Local |
0.953 |
0.003 |
Inf |
0.947 |
0.959 |
| RVF |
Global |
0.972 |
0.002 |
Inf |
0.968 |
0.976 |
| RVF |
Local |
0.958 |
0.003 |
Inf |
0.952 |
0.963 |
| field |
level |
mean_subject_percent_correct |
| LVF |
Global |
97.394 |
| LVF |
Local |
92.995 |
| RVF |
Global |
95.629 |
| RVF |
Local |
93.627 |